Direct calculation of relative binding affinities between antibodies and antigens is a long-sought goal. However, despite substantial efforts, no generally applicable computational method has been described. Here, we describe a systematic free energy perturbation (FEP) protocol and calculate the binding affinities between the gp120 envelope glycoprotein of HIV-1 and three broadly neutralizing antibodies (bNAbs) of the VRC01 class. The protocol has been adapted from successful studies of small molecules to address the challenges associated with modeling protein&ndash;protein interactions. Specifically, we built homology models of the three antibody&ndash;gp120 complexes, extended the sampling times for large bulky residues, incorporated the modeling of glycans on the surface of gp120, and utilized continuum solvent-based loop prediction protocols to improve sampling. We present three experimental surface plasmon resonance data sets, in which antibody residues in the antibody/gp120 interface were systematically mutated to alanine. The RMS error in the large set (55 total cases) of FEP tests as compared to these experiments, 0.68&nbsp;kcal/mol, is near experimental accuracy, and it compares favorably with the results obtained from a simpler, empirical methodology. The correlation coefficient for the combined data set including residues with glycan contacts, R2&nbsp;=&nbsp;0.49, should be sufficient to guide the choice of residues for antibody optimization projects, assuming that this level of accuracy can be realized in prospective prediction. More generally, these results are encouraging with regard to the possibility of using an FEP approach to calculate the magnitude of protein&ndash;protein binding affinities.

Mentions:
Three VRC01-class bNAbs were considered, for which experimental alanine scans with quantification of binding affinities using an Octet biosensor were performed (Table S1 in the Supplementary Data): VRC01 and VRC03 [10]—members of the same antibody lineage from NIAID donor 45—and VRC-PG04 from IAVI protocol G donor 74 [4]. Briefly, antibodies and mutants were bound to the Octet tip surface, and core gp120 were passed over the surface and sensograms recorded. Kds were determined by fitting to a 1:1 binding model (see Models and Methods). Estimated binding free energies typically fell within an uncertainty range of about 0.5 kcal/mol (see Table S2 of the Supplementary Data for details). Figure 1 presents all of the sites of mutation experimentally studied for each of the three antibodies listed above.

Mentions:
Three VRC01-class bNAbs were considered, for which experimental alanine scans with quantification of binding affinities using an Octet biosensor were performed (Table S1 in the Supplementary Data): VRC01 and VRC03 [10]—members of the same antibody lineage from NIAID donor 45—and VRC-PG04 from IAVI protocol G donor 74 [4]. Briefly, antibodies and mutants were bound to the Octet tip surface, and core gp120 were passed over the surface and sensograms recorded. Kds were determined by fitting to a 1:1 binding model (see Models and Methods). Estimated binding free energies typically fell within an uncertainty range of about 0.5 kcal/mol (see Table S2 of the Supplementary Data for details). Figure 1 presents all of the sites of mutation experimentally studied for each of the three antibodies listed above.

Direct calculation of relative binding affinities between antibodies and antigens is a long-sought goal. However, despite substantial efforts, no generally applicable computational method has been described. Here, we describe a systematic free energy perturbation (FEP) protocol and calculate the binding affinities between the gp120 envelope glycoprotein of HIV-1 and three broadly neutralizing antibodies (bNAbs) of the VRC01 class. The protocol has been adapted from successful studies of small molecules to address the challenges associated with modeling protein&ndash;protein interactions. Specifically, we built homology models of the three antibody&ndash;gp120 complexes, extended the sampling times for large bulky residues, incorporated the modeling of glycans on the surface of gp120, and utilized continuum solvent-based loop prediction protocols to improve sampling. We present three experimental surface plasmon resonance data sets, in which antibody residues in the antibody/gp120 interface were systematically mutated to alanine. The RMS error in the large set (55 total cases) of FEP tests as compared to these experiments, 0.68&nbsp;kcal/mol, is near experimental accuracy, and it compares favorably with the results obtained from a simpler, empirical methodology. The correlation coefficient for the combined data set including residues with glycan contacts, R2&nbsp;=&nbsp;0.49, should be sufficient to guide the choice of residues for antibody optimization projects, assuming that this level of accuracy can be realized in prospective prediction. More generally, these results are encouraging with regard to the possibility of using an FEP approach to calculate the magnitude of protein&ndash;protein binding affinities.